Literature DB >> 33685944

Brain Activity Foreshadows Stock Price Dynamics.

Mirre Stallen1, Nicholas Borg2, Brian Knutson1.   

Abstract

Successful investing is challenging since stock prices are difficult to consistently forecast. Recent neuroimaging evidence suggests, however, that activity in brain regions associated with anticipatory affect may not only predict individual choice, but also forecast aggregate behavior out-of-sample. Thus, in two experiments, we specifically tested whether anticipatory affective brain activity in healthy humans could forecast aggregate changes in stock prices. Using functional magnetic resonance imaging, we found in a first experiment (n = 34, 6 females; 140 trials/subject) that nucleus accumbens activity forecast stock price direction, whereas anterior insula (AIns) activity forecast stock price inflections. In a second preregistered replication experiment (n = 39, 7 females) that included different subjects and stocks, AIns activity still forecast stock price inflections. Importantly, AIns activity forecast stock price movement even when choice behavior and conventional stock indicators did not (e.g., previous stock price movements), and classifier analysis indicated that forecasts based on brain activity should generalize to other markets. By demonstrating that AIns activity might serve as a leading indicator of stock price inflections, these findings imply that neural activity associated with anticipatory affect may extend to forecasting aggregate choice in dynamic and competitive environments such as stock markets.SIGNIFICANCE STATEMENT Many try but fail to consistently forecast changes in stock prices. New evidence, however, suggests that anticipatory affective brain activity may not only predict individual choice, but also may forecast aggregate choice. Assuming that stock prices index collective choice, we tested whether brain activity sampled during the assessment of stock prices could forecast subsequent changes in the prices of those stocks. In two neuroimaging experiments, a combination of previous stock price movements and brain activity in a region implicated in processing uncertainty and arousal forecast next-day stock price changes-even when behavior did not. These findings challenge traditional assumptions of market efficiency by implying that neuroimaging data might reveal "hidden information" capable of foreshadowing stock price dynamics.
Copyright © 2021 Stallen et al.

Entities:  

Keywords:  accumbens; choice; decision; financial; forecast; insula

Year:  2021        PMID: 33685944      PMCID: PMC8026346          DOI: 10.1523/JNEUROSCI.1727-20.2021

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  28 in total

1.  Neural activity in the human brain relating to uncertainty and arousal during anticipation.

Authors:  H D Critchley; C J Mathias; R J Dolan
Journal:  Neuron       Date:  2001-02       Impact factor: 17.173

2.  Risk as feelings.

Authors:  G F Loewenstein; E U Weber; C K Hsee; N Welch
Journal:  Psychol Bull       Date:  2001-03       Impact factor: 17.737

3.  Neural signature of fictive learning signals in a sequential investment task.

Authors:  Terry Lohrenz; Kevin McCabe; Colin F Camerer; P Read Montague
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-22       Impact factor: 11.205

Review 4.  The reward circuit: linking primate anatomy and human imaging.

Authors:  Suzanne N Haber; Brian Knutson
Journal:  Neuropsychopharmacology       Date:  2010-01       Impact factor: 7.853

5.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.

Authors:  R W Cox
Journal:  Comput Biomed Res       Date:  1996-06

6.  Ventromedial frontal lobe damage disrupts value maximization in humans.

Authors:  Nathalie Camille; Cathryn A Griffiths; Khoi Vo; Lesley K Fellows; Joseph W Kable
Journal:  J Neurosci       Date:  2011-05-18       Impact factor: 6.167

7.  From neural responses to population behavior: neural focus group predicts population-level media effects.

Authors:  Emily B Falk; Elliot T Berkman; Matthew D Lieberman
Journal:  Psychol Sci       Date:  2012-04-17

8.  Using Neural Data to Test A Theory of Investor Behavior: An Application to Realization Utility.

Authors:  Cary Frydman; Nicholas Barberis; Colin Camerer; Peter Bossaerts; Antonio Rangel
Journal:  J Finance       Date:  2014-04-01

9.  Gain and loss learning differentially contribute to life financial outcomes.

Authors:  Brian Knutson; Gregory R Samanez-Larkin; Camelia M Kuhnen
Journal:  PLoS One       Date:  2011-09-06       Impact factor: 3.240

10.  In the mind of the market: theory of mind biases value computation during financial bubbles.

Authors:  Benedetto De Martino; John P O'Doherty; Debajyoti Ray; Peter Bossaerts; Colin Camerer
Journal:  Neuron       Date:  2013-09-18       Impact factor: 17.173

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.